TY - JOUR
AB - The theory of persistent homology opens up the possibility to reason about topological features of a space or a function quantitatively and in combinatorial terms. We refer to this new angle at a classical subject within algebraic topology as a point calculus, which we present for the family of interlevel sets of a real-valued function. Our account of the subject is expository, devoid of proofs, and written for non-experts in algebraic topology.
AU - Bendich, Paul
AU - Cabello, Sergio
AU - Edelsbrunner, Herbert
ID - 3310
IS - 11
JF - Pattern Recognition Letters
TI - A point calculus for interlevel set homology
VL - 33
ER -
TY - JOUR
AB - Computing the topology of an algebraic plane curve C means computing a combinatorial graph that is isotopic to C and thus represents its topology in R2. We prove that, for a polynomial of degree n with integer coefficients bounded by 2ρ, the topology of the induced curve can be computed with bit operations ( indicates that we omit logarithmic factors). Our analysis improves the previous best known complexity bounds by a factor of n2. The improvement is based on new techniques to compute and refine isolating intervals for the real roots of polynomials, and on the consequent amortized analysis of the critical fibers of the algebraic curve.
AU - Kerber, Michael
AU - Sagraloff, Michael
ID - 3331
IS - 3
JF - Journal of Symbolic Computation
TI - A worst case bound for topology computation of algebraic curves
VL - 47
ER -
TY - JOUR
AB - First we note that the best polynomial approximation to vertical bar x vertical bar on the set, which consists of an interval on the positive half-axis and a point on the negative half-axis, can be given by means of the classical Chebyshev polynomials. Then we explore the cases when a solution of the related problem on two intervals can be given in elementary functions.
AU - Pausinger, Florian
ID - 6588
IS - 1
JF - Journal of Mathematical Physics, Analysis, Geometry
SN - 1812-9471
TI - Elementary solutions of the Bernstein problem on two intervals
VL - 8
ER -
TY - CONF
AB - It has been an open question whether the sum of finitely many isotropic Gaussian kernels in n ≥ 2 dimensions can have more modes than kernels, until in 2003 Carreira-Perpiñán and Williams exhibited n +1 isotropic Gaussian kernels in ℝ n with n + 2 modes. We give a detailed analysis of this example, showing that it has exponentially many critical points and that the resilience of the extra mode grows like √n. In addition, we exhibit finite configurations of isotropic Gaussian kernels with superlinearly many modes.
AU - Edelsbrunner, Herbert
AU - Fasy, Brittany
AU - Rote, Günter
ID - 3134
T2 - Proceedings of the twenty-eighth annual symposium on Computational geometry
TI - Add isotropic Gaussian kernels at own risk: More and more resilient modes in higher dimensions
ER -
TY - CONF
AB - We present a joint image segmentation and labeling model (JSL) which, given a bag of figure-ground segment hypotheses extracted at multiple image locations and scales, constructs a joint probability distribution over both the compatible image interpretations (tilings or image segmentations) composed from those segments, and over their labeling into categories. The process of drawing samples from the joint distribution can be interpreted as first sampling tilings, modeled as maximal cliques, from a graph connecting spatially non-overlapping segments in the bag [1], followed by sampling labels for those segments, conditioned on the choice of a particular tiling. We learn the segmentation and labeling parameters jointly, based on Maximum Likelihood with a novel Incremental Saddle Point estimation procedure. The partition function over tilings and labelings is increasingly more accurately approximated by including incorrect configurations that a not-yet-competent model rates probable during learning. We show that the proposed methodologymatches the current state of the art in the Stanford dataset [2], as well as in VOC2010, where 41.7% accuracy on the test set is achieved.
AU - Ion, Adrian
AU - Carreira, Joao
AU - Sminchisescu, Cristian
ID - 3266
T2 - NIPS Proceedings
TI - Probabilistic joint image segmentation and labeling
VL - 24
ER -
TY - JOUR
AB - The unintentional scattering of light between neighboring surfaces in complex projection environments increases the brightness and decreases the contrast, disrupting the appearance of the desired imagery. To achieve satisfactory projection results, the inverse problem of global illumination must be solved to cancel this secondary scattering. In this paper, we propose a global illumination cancellation method that minimizes the perceptual difference between the desired imagery and the actual total illumination in the resulting physical environment. Using Gauss-Newton and active set methods, we design a fast solver for the bound constrained nonlinear least squares problem raised by the perceptual error metrics. Our solver is further accelerated with a CUDA implementation and multi-resolution method to achieve 1–2 fps for problems with approximately 3000 variables. We demonstrate the global illumination cancellation algorithm with our multi-projector system. Results show that our method preserves the color fidelity of the desired imagery significantly better than previous methods.
AU - Sheng, Yu
AU - Cutler, Barbara
AU - Chen, Chao
AU - Nasman, Joshua
ID - 3269
IS - 4
JF - Computer Graphics Forum
TI - Perceptual global illumination cancellation in complex projection environments
VL - 30
ER -
TY - CONF
AB - The persistence diagram of a filtered simplicial com- plex is usually computed by reducing the boundary matrix of the complex. We introduce a simple op- timization technique: by processing the simplices of the complex in decreasing dimension, we can “kill” columns (i.e., set them to zero) without reducing them. This technique completely avoids reduction on roughly half of the columns. We demonstrate that this idea significantly improves the running time of the reduction algorithm in practice. We also give an output-sensitive complexity analysis for the new al- gorithm which yields to sub-cubic asymptotic bounds under certain assumptions.
AU - Chen, Chao
AU - Kerber, Michael
ID - 3270
TI - Persistent homology computation with a twist
ER -
TY - CHAP
AB - In this paper we present an efficient framework for computation of persis- tent homology of cubical data in arbitrary dimensions. An existing algorithm using simplicial complexes is adapted to the setting of cubical complexes. The proposed approach enables efficient application of persistent homology in domains where the data is naturally given in a cubical form. By avoiding triangulation of the data, we significantly reduce the size of the complex. We also present a data-structure de- signed to compactly store and quickly manipulate cubical complexes. By means of numerical experiments, we show high speed and memory efficiency of our ap- proach. We compare our framework to other available implementations, showing its superiority. Finally, we report performance on selected 3D and 4D data-sets.
AU - Wagner, Hubert
AU - Chen, Chao
AU - Vuçini, Erald
ED - Peikert, Ronald
ED - Hauser, Helwig
ED - Carr, Hamish
ED - Fuchs, Raphael
ID - 3271
T2 - Topological Methods in Data Analysis and Visualization II
TI - Efficient computation of persistent homology for cubical data
ER -
TY - GEN
AB - We study the 3D reconstruction of plant roots from multiple 2D images. To meet the challenge caused by the delicate nature of thin branches, we make three innovations to cope with the sensitivity to image quality and calibration. First, we model the background as a harmonic function to improve the segmentation of the root in each 2D image. Second, we develop the concept of the regularized visual hull which reduces the effect of jittering and refraction by ensuring consistency with one 2D image. Third, we guarantee connectedness through adjustments to the 3D reconstruction that minimize global error. Our software is part of a biological phenotype/genotype study of agricultural root systems. It has been tested on more than 40 plant roots and results are promising in terms of reconstruction quality and efficiency.
AU - Zheng, Ying
AU - Gu, Steve
AU - Edelsbrunner, Herbert
AU - Tomasi, Carlo
AU - Benfey, Philip
ID - 3312
T2 - Proceedings of the IEEE International Conference on Computer Vision
TI - Detailed reconstruction of 3D plant root shape
ER -
TY - CONF
AB - Interpreting an image as a function on a compact sub- set of the Euclidean plane, we get its scale-space by diffu- sion, spreading the image over the entire plane. This gener- ates a 1-parameter family of functions alternatively defined as convolutions with a progressively wider Gaussian ker- nel. We prove that the corresponding 1-parameter family of persistence diagrams have norms that go rapidly to zero as time goes to infinity. This result rationalizes experimental observations about scale-space. We hope this will lead to targeted improvements of related computer vision methods.
AU - Chen, Chao
AU - Edelsbrunner, Herbert
ID - 3313
T2 - Proceedings of the IEEE International Conference on Computer Vision
TI - Diffusion runs low on persistence fast
ER -
TY - CONF
AB - We report on a generic uni- and bivariate algebraic kernel that is publicly available with CGAL 3.7. It comprises complete, correct, though efficient state-of-the-art implementations on polynomials, roots of polynomial systems, and the support to analyze algebraic curves defined by bivariate polynomials. The kernel design is generic, that is, various number types and substeps can be exchanged. It is accompanied with a ready-to-use interface to enable arrangements induced by algebraic curves, that have already been used as basis for various geometric applications, as arrangements on Dupin cyclides or the triangulation of algebraic surfaces. We present two novel applications: arrangements of rotated algebraic curves and Boolean set operations on polygons bounded by segments of algebraic curves. We also provide experiments showing that our general implementation is competitive and even often clearly outperforms existing implementations that are explicitly tailored for specific types of non-linear curves that are available in CGAL.
AU - Berberich, Eric
AU - Hemmer, Michael
AU - Kerber, Michael
ID - 3328
TI - A generic algebraic kernel for non linear geometric applications
ER -
TY - CONF
AB - We consider the offset-deconstruction problem: Given a polygonal shape Q with n vertices, can it be expressed, up to a tolerance µ in Hausdorff distance, as the Minkowski sum of another polygonal shape P with a disk of fixed radius? If it does, we also seek a preferably simple-looking solution shape P; then, P's offset constitutes an accurate, vertex-reduced, and smoothened approximation of Q. We give an O(n log n)-time exact decision algorithm that handles any polygonal shape, assuming the real-RAM model of computation. An alternative algorithm, based purely on rational arithmetic, answers the same deconstruction problem, up to an uncertainty parameter, and its running time depends on the parameter δ (in addition to the other input parameters: n, δ and the radius of the disk). If the input shape is found to be approximable, the rational-arithmetic algorithm also computes an approximate solution shape for the problem. For convex shapes, the complexity of the exact decision algorithm drops to O(n), which is also the time required to compute a solution shape P with at most one more vertex than a vertex-minimal one. Our study is motivated by applications from two different domains. However, since the offset operation has numerous uses, we anticipate that the reverse question that we study here will be still more broadly applicable. We present results obtained with our implementation of the rational-arithmetic algorithm.
AU - Berberich, Eric
AU - Halperin, Dan
AU - Kerber, Michael
AU - Pogalnikova, Roza
ID - 3329
T2 - Proceedings of the twenty-seventh annual symposium on Computational geometry
TI - Deconstructing approximate offsets
ER -
TY - CONF
AB - We consider the problem of approximating all real roots of a square-free polynomial f. Given isolating intervals, our algorithm refines each of them to a width at most 2-L, that is, each of the roots is approximated to L bits after the binary point. Our method provides a certified answer for arbitrary real polynomials, only requiring finite approximations of the polynomial coefficient and choosing a suitable working precision adaptively. In this way, we get a correct algorithm that is simple to implement and practically efficient. Our algorithm uses the quadratic interval refinement method; we adapt that method to be able to cope with inaccuracies when evaluating f, without sacrificing its quadratic convergence behavior. We prove a bound on the bit complexity of our algorithm in terms of degree, coefficient size and discriminant. Our bound improves previous work on integer polynomials by a factor of deg f and essentially matches best known theoretical bounds on root approximation which are obtained by very sophisticated algorithms.
AU - Kerber, Michael
AU - Sagraloff, Michael
ID - 3330
TI - Root refinement for real polynomials
ER -
TY - JOUR
AB - Given an algebraic hypersurface O in ℝd, how many simplices are necessary for a simplicial complex isotopic to O? We address this problem and the variant where all vertices of the complex must lie on O. We give asymptotically tight worst-case bounds for algebraic plane curves. Our results gradually improve known bounds in higher dimensions; however, the question for tight bounds remains unsolved for d ≥ 3.
AU - Kerber, Michael
AU - Sagraloff, Michael
ID - 3332
IS - 3
JF - Graphs and Combinatorics
TI - A note on the complexity of real algebraic hypersurfaces
VL - 27
ER -
TY - JOUR
AU - Edelsbrunner, Herbert
AU - Pach, János
AU - Ziegler, Günter
ID - 3334
IS - 1
JF - Discrete & Computational Geometry
TI - Letter from the new editors-in-chief
VL - 45
ER -
TY - CHAP
AB - We study the topology of the Megaparsec Cosmic Web in terms of the scale-dependent Betti numbers, which formalize the topological information content of the cosmic mass distribution. While the Betti numbers do not fully quantify topology, they extend the information beyond conventional cosmological studies of topology in terms of genus and Euler characteristic. The richer information content of Betti numbers goes along the availability of fast algorithms to compute them. For continuous density fields, we determine the scale-dependence of Betti numbers by invoking the cosmologically familiar filtration of sublevel or superlevel sets defined by density thresholds. For the discrete galaxy distribution, however, the analysis is based on the alpha shapes of the particles. These simplicial complexes constitute an ordered sequence of nested subsets of the Delaunay tessellation, a filtration defined by the scale parameter, α. As they are homotopy equivalent to the sublevel sets of the distance field, they are an excellent tool for assessing the topological structure of a discrete point distribution. In order to develop an intuitive understanding for the behavior of Betti numbers as a function of α, and their relation to the morphological patterns in the Cosmic Web, we first study them within the context of simple heuristic Voronoi clustering models. These can be tuned to consist of specific morphological elements of the Cosmic Web, i.e. clusters, filaments, or sheets. To elucidate the relative prominence of the various Betti numbers in different stages of morphological evolution, we introduce the concept of alpha tracks. Subsequently, we address the topology of structures emerging in the standard LCDM scenario and in cosmological scenarios with alternative dark energy content. The evolution of the Betti numbers is shown to reflect the hierarchical evolution of the Cosmic Web. We also demonstrate that the scale-dependence of the Betti numbers yields a promising measure of cosmological parameters, with a potential to help in determining the nature of dark energy and to probe primordial non-Gaussianities. We also discuss the expected Betti numbers as a function of the density threshold for superlevel sets of a Gaussian random field. Finally, we introduce the concept of persistent homology. It measures scale levels of the mass distribution and allows us to separate small from large scale features. Within the context of the hierarchical cosmic structure formation, persistence provides a natural formalism for a multiscale topology study of the Cosmic Web.
AU - Van De Weygaert, Rien
AU - Vegter, Gert
AU - Edelsbrunner, Herbert
AU - Jones, Bernard
AU - Pranav, Pratyush
AU - Park, Changbom
AU - Hellwing, Wojciech
AU - Eldering, Bob
AU - Kruithof, Nico
AU - Bos, Patrick
AU - Hidding, Johan
AU - Feldbrugge, Job
AU - Ten Have, Eline
AU - Van Engelen, Matti
AU - Caroli, Manuel
AU - Teillaud, Monique
ED - Gavrilova, Marina
ED - Tan, Kenneth
ED - Mostafavi, Mir
ID - 3335
T2 - Transactions on Computational Science XIV
TI - Alpha, Betti and the Megaparsec Universe: On the topology of the Cosmic Web
VL - 6970
ER -
TY - CONF
AB - In this paper, we present the first output-sensitive algorithm to compute the persistence diagram of a filtered simplicial complex. For any Γ>0, it returns only those homology classes with persistence at least Γ. Instead of the classical reduction via column operations, our algorithm performs rank computations on submatrices of the boundary matrix. For an arbitrary constant δ ∈ (0,1), the running time is O(C(1-δ)ΓR(n)log n), where C(1-δ)Γ is the number of homology classes with persistence at least (1-δ)Γ, n is the total number of simplices, and R(n) is the complexity of computing the rank of an n x n matrix with O(n) nonzero entries. Depending on the choice of the rank algorithm, this yields a deterministic O(C(1-δ)Γn2.376) algorithm, a O(C(1-δ)Γn2.28) Las-Vegas algorithm, or a O(C(1-δ)Γn2+ε) Monte-Carlo algorithm for an arbitrary ε>0.
AU - Chen, Chao
AU - Kerber, Michael
ID - 3367
TI - An output sensitive algorithm for persistent homology
ER -
TY - JOUR
AB - By definition, transverse intersections are stable under in- finitesimal perturbations. Using persistent homology, we ex- tend this notion to sizeable perturbations. Specifically, we assign to each homology class of the intersection its robust- ness, the magnitude of a perturbation necessary to kill it, and prove that robustness is stable. Among the applications of this result is a stable notion of robustness for fixed points of continuous mappings and a statement of stability for con- tours of smooth mappings.
AU - Edelsbrunner, Herbert
AU - Morozov, Dmitriy
AU - Patel, Amit
ID - 3377
IS - 3
JF - Foundations of Computational Mathematics
TI - Quantifying transversality by measuring the robustness of intersections
VL - 11
ER -
TY - JOUR
AB - The theory of intersection homology was developed to study the singularities of a topologically stratified space. This paper in- corporates this theory into the already developed framework of persistent homology. We demonstrate that persistent intersec- tion homology gives useful information about the relationship between an embedded stratified space and its singularities. We give, and prove the correctness of, an algorithm for the computa- tion of the persistent intersection homology groups of a filtered simplicial complex equipped with a stratification by subcom- plexes. We also derive, from Poincare ́ Duality, some structural results about persistent intersection homology.
AU - Bendich, Paul
AU - Harer, John
ID - 3378
IS - 3
JF - Foundations of Computational Mathematics
TI - Persistent intersection homology
VL - 11
ER -
TY - CONF
AB - In this paper, we establish a correspondence between the incremental algorithm for computing AT-models [8,9] and the one for computing persistent homology [6,14,15]. We also present a decremental algorithm for computing AT-models that allows to extend the persistence computation to a wider setting. Finally, we show how to combine incremental and decremental techniques for persistent homology computation.
AU - Gonzalez-Diaz, Rocio
AU - Ion, Adrian
AU - Jimenez, Maria Jose
AU - Poyatos, Regina
ID - 9648
SN - 03029743
T2 - Computer Analysis of Images and Patterns
TI - Incremental-decremental algorithm for computing AT-models and persistent homology
VL - 6854
ER -
TY - JOUR
AB - We bound the difference in length of two curves in terms of their total curvatures and the Fréchet distance. The bound is independent of the dimension of the ambient Euclidean space, it improves upon a bound by Cohen-Steiner and Edelsbrunner, and it generalizes a result by Fáry and Chakerian.
AU - Fasy, Brittany Terese
ID - 3781
IS - 1-2
JF - Acta Sci. Math. (Szeged)
TI - The difference in length of curves in R^n
VL - 77
ER -
TY - CHAP
AB - We address the problem of covering ℝ n with congruent balls, while minimizing the number of balls that contain an average point. Considering the 1-parameter family of lattices defined by stretching or compressing the integer grid in diagonal direction, we give a closed formula for the covering density that depends on the distortion parameter. We observe that our family contains the thinnest lattice coverings in dimensions 2 to 5. We also consider the problem of packing congruent balls in ℝ n , for which we give a closed formula for the packing density as well. Again we observe that our family contains optimal configurations, this time densest packings in dimensions 2 and 3.
AU - Edelsbrunner, Herbert
AU - Kerber, Michael
ED - Calude, Cristian
ED - Rozenberg, Grzegorz
ED - Salomaa, Arto
ID - 3796
T2 - Rainbow of Computer Science
TI - Covering and packing with spheres by diagonal distortion in R^n
VL - 6570
ER -
TY - JOUR
AB - The elevation function on a smoothly embedded 2-manifold in R-3 reflects the multiscale topography of cavities and protrusions as local maxima. The function has been useful in identifying coarse docking configurations for protein pairs. Transporting the concept from the smooth to the piecewise linear category, this paper describes an algorithm for finding all local maxima. While its worst-case running time is the same as of the algorithm used in prior work, its performance in practice is orders of magnitudes superior. We cast light on this improvement by relating the running time to the total absolute Gaussian curvature of the 2-manifold.
AU - Wang, Bei
AU - Edelsbrunner, Herbert
AU - Morozov, Dmitriy
ID - 3965
IS - 2.2
JF - Journal of Experimental Algorithmics
TI - Computing elevation maxima by searching the Gauss sphere
VL - 16
ER -
TY - JOUR
AB - We address the problem of localizing homology classes, namely, finding the cycle representing a given class with the most concise geometric measure. We study the problem with different measures: volume, diameter and radius. For volume, that is, the 1-norm of a cycle, two main results are presented. First, we prove that the problem is NP-hard to approximate within any constant factor. Second, we prove that for homology of dimension two or higher, the problem is NP-hard to approximate even when the Betti number is O(1). The latter result leads to the inapproximability of the problem of computing the nonbounding cycle with the smallest volume and computing cycles representing a homology basis with the minimal total volume. As for the other two measures defined by pairwise geodesic distance, diameter and radius, we show that the localization problem is NP-hard for diameter but is polynomial for radius. Our work is restricted to homology over the ℤ2 field.
AU - Chen, Chao
AU - Freedman, Daniel
ID - 3267
IS - 3
JF - Discrete & Computational Geometry
TI - Hardness results for homology localization
VL - 45
ER -
TY - CONF
AB - We introduce TopoCut: a new way to integrate knowledge about topological properties (TPs) into random field image segmentation model. Instead of including TPs as additional constraints during minimization of the energy function, we devise an efficient algorithm for modifying the unary potentials such that the resulting segmentation is guaranteed with the desired properties. Our method is more flexible in the sense that it handles more topology constraints than previous methods, which were only able to enforce pairwise or global connectivity. In particular, our method is very fast, making it for the first time possible to enforce global topological properties in practical image segmentation tasks.
AU - Chen, Chao
AU - Freedman, Daniel
AU - Lampert, Christoph
ID - 3336
SN - 978-1-4577-0394-2
T2 - CVPR: Computer Vision and Pattern Recognition
TI - Enforcing topological constraints in random field image segmentation
ER -
TY - CHAP
AB - Alpha shapes have been conceived in 1981 as an attempt to define the shape of a finite set of point in the plane. Since then, connections to diverse areas in the sciences and engineering have developed, including to pattern recognition, digital shape sampling and processing, and structural molecular biology. This survey begins with a historical account and discusses geometric, algorithmic, topological, and combinatorial aspects of alpha shapes in this sequence.
AU - Edelsbrunner, Herbert
ED - van de Weygaert, R
ED - Vegter, G
ED - Ritzerveld, J
ED - Icke, V
ID - 3311
T2 - Tessellations in the Sciences: Virtues, Techniques and Applications of Geometric Tilings
TI - Alpha shapes - a survey
ER -
TY - CONF
AB - This paper presents a method to create a model of an articulated object using the planar motion in an initialization video. The model consists of rigid parts connected by points of articulation. The rigid parts are described by the positions of salient feature-points tracked throughout the video. Following a filtering step that identifies points that belong to different objects, rigid parts are found by a grouping process in a graph pyramid. Valid articulation points are selected by verifying multiple hypotheses for each pair of parts.
AU - Artner, Nicole M.
AU - Ion, Adrian
AU - Kropatsch, Walter G.
ED - Jiang, Xiaoyi
ED - Ferrer, Miquel
ED - Torsello, Andrea
ID - 10907
SN - 0302-9743
T2 - Graph-Based Representations in Pattern Recognition
TI - Spatio-temporal extraction of articulated models in a graph pyramid
VL - 6658
ER -
TY - CONF
AB - In cortex surface segmentation, the extracted surface is required to have a particular topology, namely, a two-sphere. We present a new method for removing topology noise of a curve or surface within the level set framework, and thus produce a cortical surface with correct topology. We define a new energy term which quantifies topology noise. We then show how to minimize this term by computing its functional derivative with respect to the level set function. This method differs from existing methods in that it is inherently continuous and not digital; and in the way that our energy directly relates to the topology of the underlying curve or surface, versus existing knot-based measures which are related in a more indirect fashion. The proposed flow is validated empirically.
AU - Chen, Chao
AU - Freedman, Daniel
ID - 3782
T2 - Conference proceedings MCV 2010
TI - Topology noise removal for curve and surface evolution
VL - 6533
ER -
TY - CHAP
AB - The (apparent) contour of a smooth mapping from a 2-manifold to the plane, f: M → R2 , is the set of critical values, that is, the image of the points at which the gradients of the two component functions are linearly dependent. Assuming M is compact and orientable and measuring difference with the erosion distance, we prove that the contour is stable.
AU - Edelsbrunner, Herbert
AU - Morozov, Dmitriy
AU - Patel, Amit
ID - 3795
T2 - Topological Data Analysis and Visualization: Theory, Algorithms and Applications
TI - The stability of the apparent contour of an orientable 2-manifold
ER -
TY - CONF
AB - We define the robustness of a level set homology class of a function f:XR as the magnitude of a perturbation necessary to kill the class. Casting this notion into a group theoretic framework, we compute the robustness for each class, using a connection to extended persistent homology. The special case X=R3 has ramifications in medical imaging and scientific visualization.
AU - Bendich, Paul
AU - Edelsbrunner, Herbert
AU - Morozov, Dmitriy
AU - Patel, Amit
ID - 3848
TI - The robustness of level sets
VL - 6346
ER -
TY - CONF
AB - Using ideas from persistent homology, the robustness of a level set of a real-valued function is defined in terms of the magnitude of the perturbation necessary to kill the classes. Prior work has shown that the homology and robustness information can be read off the extended persistence diagram of the function. This paper extends these results to a non-uniform error model in which perturbations vary in their magnitude across the domain.
AU - Bendich, Paul
AU - Edelsbrunner, Herbert
AU - Kerber, Michael
AU - Patel, Amit
ID - 3849
TI - Persistent homology under non-uniform error
VL - 6281
ER -
TY - CONF
AB - Given a polygonal shape Q with n vertices, can it be expressed, up to a tolerance ε in Hausdorff distance, as the Minkowski sum of another polygonal shape with a disk of fixed radius? If it does, we also seek a preferably simple solution shape P;P’s offset constitutes an accurate, vertex-reduced, and smoothened approximation of Q. We give a decision algorithm for fixed radius in O(nlogn) time that handles any polygonal shape. For convex shapes, the complexity drops to O(n), which is also the time required to compute a solution shape P with at most one more vertex than a vertex-minimal one.
AU - Berberich, Eric
AU - Halperin, Dan
AU - Kerber, Michael
AU - Pogalnikova, Roza
ID - 3850
TI - Polygonal reconstruction from approximate offsets
ER -
TY - CONF
AB - Quantitative languages are an extension of boolean languages that assign to each word a real number. Mean-payoff automata are finite automata with numerical weights on transitions that assign to each infinite path the long-run average of the transition weights. When the mode of branching of the automaton is deterministic, nondeterministic, or alternating, the corresponding class of quantitative languages is not robust as it is not closed under the pointwise operations of max, min, sum, and numerical complement. Nondeterministic and alternating mean-payoff automata are not decidable either, as the quantitative generalization of the problems of universality and language inclusion is undecidable. We introduce a new class of quantitative languages, defined by mean-payoff automaton expressions, which is robust and decidable: it is closed under the four pointwise operations, and we show that all decision problems are decidable for this class. Mean-payoff automaton expressions subsume deterministic meanpayoff automata, and we show that they have expressive power incomparable to nondeterministic and alternating mean-payoff automata. We also present for the first time an algorithm to compute distance between two quantitative languages, and in our case the quantitative languages are given as mean-payoff automaton expressions.
AU - Chatterjee, Krishnendu
AU - Doyen, Laurent
AU - Edelsbrunner, Herbert
AU - Henzinger, Thomas A
AU - Rannou, Philippe
ID - 3853
TI - Mean-payoff automaton expressions
VL - 6269
ER -
TY - JOUR
AB - We are interested in 3-dimensional images given as arrays of voxels with intensity values. Extending these values to acontinuous function, we study the robustness of homology classes in its level and interlevel sets, that is, the amount of perturbationneeded to destroy these classes. The structure of the homology classes and their robustness, over all level and interlevel sets, can bevisualized by a triangular diagram of dots obtained by computing the extended persistence of the function. We give a fast hierarchicalalgorithm using the dual complexes of oct-tree approximations of the function. In addition, we show that for balanced oct-trees, thedual complexes are geometrically realized in $R^3$ and can thus be used to construct level and interlevel sets. We apply these tools tostudy 3-dimensional images of plant root systems.
AU - Bendich, Paul
AU - Edelsbrunner, Herbert
AU - Kerber, Michael
ID - 3901
IS - 6
JF - IEEE Transactions of Visualization and Computer Graphics
TI - Computing robustness and persistence for images
VL - 16
ER -
TY - CONF
AB - We address the problem of localizing homology classes, namely, finding the cycle representing a given class with the most concise geometric measure. We focus on the volume measure, that is, the 1-norm of a cycle. Two main results are presented. First, we prove the problem is NP-hard to approximate within any constant factor. Second, we prove that for homology of dimension two or higher, the problem is NP-hard to approximate even when the Betti number is O(1). A side effect is the inapproximability of the problem of computing the nonbounding cycle with the smallest volume, and computing cycles representing a homology basis with the minimal total volume. We also discuss other geometric measures (diameter and radius) and show their disadvantages in homology localization. Our work is restricted to homology over the ℤ2 field.
AU - Chen, Chao
AU - Freedman, Daniel
ID - 10909
T2 - Proceedings of the 2010 Annual ACM-SIAM Symposium on Discrete Algorithms
TI - Hardness results for homology localization
ER -
TY - CONF
AB - We describe an algorithm for segmenting three-dimensional medical imaging data modeled as a continuous function on a 3-manifold. It is related to watershed algorithms developed in image processing but is closer to its mathematical roots, which are Morse theory and homological algebra. It allows for the implicit treatment of an underlying mesh, thus combining the structural integrity of its mathematical foundations with the computational efficiency of image processing.
AU - Edelsbrunner, Herbert
AU - Harer, John
ID - 3968
TI - The persistent Morse complex segmentation of a 3-manifold
VL - 5903
ER -